code: def test_openvino_quantize_dynamic_axes(self):
      class CustomModel(nn.Module):
          def __init__(self):
              super().__init__()
              self.pool = nn.AvgPool2d(kernel_size=3, stride=3)
  
          def forward(self, x):
              return self.pool(x)
  
      model = CustomModel()
      x1 = torch.rand(1, 3, 14, 14)
      x2 = torch.rand(4, 3, 14, 14)
      x3 = torch.rand(1, 3, 12, 12)
  
      accmodel = InferenceOptimizer.quantize(
          model,
          accelerator="openvino",
          calib_data=torch.rand(1, 3, 14, 14),
      )
      accmodel(x1)
      accmodel(x2)
      try:
          accmodel(x3)
      except Exception as e:
          assert e
  
      accmodel = InferenceOptimizer.quantize(
          model,
          accelerator="openvino",
          calib_data=torch.rand(1, 3, 14, 14),
          dynamic_axes={"x": [0, 2, 3]},
      )
      accmodel(x1)
      accmodel(x2)
      accmodel(x3)
  
imports: from unittest import TestCase
  from torchmetrics import F1Score
  from bigdl.nano.pytorch import Trainer
  from bigdl.nano.pytorch import InferenceOptimizer
  from torchvision.models.mobilenetv3 import mobilenet_v3_small
  from torchvision.models import resnet50
  import torch
  from torch import nn
  from torch.utils.data.dataset import TensorDataset
  from torch.utils.data.dataloader import DataLoader
  import tempfile
  import pytest
  import numpy
label_desc: Use image node_id 7 for calling the TestOpenVINO obj's underlying member method code with example usage: obj.test_openvino_quantize_dynamic_axes() and returns: self